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HMM-applications

1. Using Hidden Markov Model to identify DNA replication timing variation regions

  • Used Continuous Density Hidden Markov Model to predict regions with high variations of DNA replication timing
  • Combined forward and backward algorithm with EM algorithm to train parameters in HMM
  • used Mix Gaussian model to estimate continuous observation density

2. Using Gibbs sampling in a Markov chain Monte Carlo approach to find motifs from sequence data

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